GA Based Adaptive Singularity-Robust Path Planning of Space Robot for On-Orbit Detection by Jianwei Wu, Deer Bin, Xiaobing Feng, Zhongpu Wen, Yin Zhang

“…Finally, in order to improve the tracking accuracy of the singularity-robust algorithm, the objective function is established, and two adaptive parameters are optimized by genetic algorithm (GA). The simulation of a 6-DOF free-floating space robot is carried out, and the results show that, compared with DLS method, the proposed method could improve the tracking accuracy of space manipulator end-effector.…”
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A Hybrid Model for Prediction in Asphalt Pavement Performance Based on Support Vector Machine and Grey Relation Analysis by Xuancang Wang, Jing Zhao, Qiqi Li, Naren Fang, Peicheng Wang, Longting Ding, Shanqiang Li

“…Meanwhile, the contrast with the grey model (GM (1, 1)), genetic algorithm optimization BP[[parms resize(1),pos(50,50),size(200,200),bgcol(156)]]081%, −0.823%, 1.270%, and −4.569%, respectively. …”
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An Efficient Genome Fragment Assembling Using GA with Neighborhood Aware Fitness Function by Satoko Kikuchi, Goutam Chakraborty

“…In this work, we have shown how our modified genetic algorithm (GA) could solve this problem efficiently. …”
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Analysis of the Modification Sensitivity of Herringbone Gear by Yong Zhao, Yajun Huang, Bin Yan, Yong Guo, Yuanyuan Zhang, Wei Cao

“…Using Romax software， genetic algorithm is used to carry out the optimal modification of tooth profile， drum shape and topology， and the modification deformation momentum is superimposed on the optimal modification. …”
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A Trajectory Planning Method for Optimal Energy Consumption of the Hydraulic Excavator by Zhang Yunyue, Sun Zhiyi, Sun Qianlai, Wang Yin, Yang Jiangtao

“…Under the constraint conditions of the joint angle, angular velocity, and angular acceleration, the improved adaptive genetic algorithm is used to optimize the uniform acceleration (deceleration) and constant velocity motion time of each joint, obtain the optimal motion curve of each joint, and realize the optimal energy consumption trajectory planning of the hydraulic excavator. …”
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Joint beam hopping and coverage control optimization algorithm for multibeam satellite system by Guoliang XU, Feng TAN, Yongyi RAN, Feng CHEN

“…To improve the performance of multibeam satellite (MBS) systems, a deep reinforcement learning-based algorithm to jointly optimize the beam hopping and coverage control (BHCC) algorithm for MBS was proposed.Firstly, the resource allocation problem in MBS was transformed to a multi-objective optimization problem with the objective maximizing the system throughput and minimizing the packet loss rate of the MBS.Secondly, the MBS environment was characterized as a multi-dimensional matrix, and the objective problem was modelled as a Markov decision process considering stochastic communication requirements.Finally, the objective problem was solved by combining the powerful feature extraction and learning capabilities of deep reinforcement learning.In addition, a single-intelligence polling multiplexing mechanism was proposed to reduce the search space and convergence difficulty and accelerate the training of BHCC.Compared with the genetic algorithm, the simulation results show that BHCC improves the throughput of MBS and reduces the packet loss rate of the system, greedy algorithm, and random algorithm.Besides, BHCC performs better in different communication scenarios compared with a deep reinforcement learning algorithm, which do not consider the adaptive beam coverage.…”
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Heston-GA Hybrid Option Pricing Model Based on ResNet50 by Zheng Yang, Liqin Zhang, Xiangxing Tao, Yanting Ji

“…Based on the optimization of Heston model parameters by genetic algorithm (GA), ResNet50 model is used to correct the deviation between market option price and Heston price, so a new hybrid option pricing model is established based on the empirical research on the European call options of Huatai-PB CSI 300ETF (code 510300), Harvest CSI 300ETF (code 159919), and SSE 50ETF (code 510050). (3) Results. …”
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Improved Population Intelligence Algorithm and BP Neural Network for Network Security Posture Prediction by Yueying Li, Feng Wu

“…Secondly, to address the problem that PSO is prone to fall into a local optimum, the genetic operator is embedded into the operation process of the particle swarm algorithm, and the excellent global optimization performance of the genetic algorithm is used to open up the spatial vision of the particle population, revive the stagnant particles, accelerate the update amplitude of the algorithm, and achieve the purpose of improving the premature problem. …”
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Fuzzy-Based Adaptive Countering Method against False Endorsement Insertion Attacks in Wireless Sensor Networks by Hae Young Lee

“…A major benefit of the proposed method is that the fuzzy systems can be optimized automatically by combining a genetic algorithm and a simulation. Thus, users only need to write a model of the WSN to apply the proposed method to a WSN. …”
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Degradation and reliability assessment of accuracy life of RV reducers by XU Hang, NIE Yixuan, WEN Dongjie, REN Jihua, HONG Zhihui

“…A Gaussian process regression model optimized by genetic algorithm was established using vibration characteristic data to optimize the prediction of transmission accuracy.ResultsThe results show that the prediction accuracy based on Gaussian process regression model is significantly better than that of traditional regression model. …”
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EXPERIMENTAL STUDY ON MILLING SURFACE QUALITY OF TC18 TITANIUM ALLOY by WANG YongXin, ZHANG ChangMing

“…Two prediction models（exponential model and multiple quadratic regression model） were established by using taguchi and optimization module design methods, and multi-objective genetic algorithm and response surface method were respectively used for parameter optimization aiming at improving surface quality and machining efficiency.The results show that: The order of influence of each parameter on the surface roughness is feed f>milling depth a_p>milling width a_e>speed of mainshaft n; The multiple quadratic regression model has higher significance and the surface topography obtained from the combination of response surface optimization parameters is optimal. …”
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Application of Modified NSGA-II to the Transit Network Design Problem by Jie Yang, Yangsheng Jiang

“…A novel initial route set generation algorithm and a route set size alternating heuristic are embedded into a nondominated sorting genetic algorithm-II- (NSGA-II-) based solution framework to produce the approximate Pareto front. …”
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Research on the Effect of DPSO in Team Selection Optimization under the Background of Big Data by Qian Zhao, Lian-ying Zhang

“…By comparing the iterative results of genetic algorithm, ordinary particle swarm algorithm, and discrete particle swarm algorithm, it is found that the DPSO algorithm is effective and preferred in the study of team selection with the background of big data.…”
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Distributed data trading algorithm based on multi-objective utility optimization by Xiaohong HUANG, Yong ZHANG, Desheng SHAN, Yekui QIAN, Lu HAN, Dandan LI, Qun CONG

“…The traditional centralized data trading models are not well applicable to the current intelligent era where everything is interconnected and real-time data is generated, and in order to maximize the use of collected data, it is essential to design an effective data trading framework.Therefore, a distributed data trading framework based on consortium blockchain was proposed, which realized P2P data trading without relying on a third party.Aiming at the problem that existing data trading models only consider the factors of the data itself and ignore the factors related to user tasks, a bi-level multi-objective optimization model was constructed based on multi-dimensional factors, such as data quality, data attributes, attribute relevance and consumer competition, to optimize the utilities of data provider (DP) and data consumer (DC).To solve the above model, an improved multi-objective genetic algorithm-collaborative NSGAII was proposed, calculated by the cooperation of DP, DC and data aggregator (AG).The simulation results show that the collaborative NSGAII achieves better performance in terms of the utilities of DP and DC, thus realizing more effective data trading.…”
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Optimal Design of Cordon Sanitaire for Regular Epidemic Control by Hongzhi Lin

“…A heuristic algorithm is designed to solve the proposed bilevel model where the method of successive averages (MSA) is adopted for the lower-level model, and the genetic algorithm (GA) is adopted for the upper-level model. …”
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Optimal Road Toll Design from the Perspective of Sustainable Development by Lin Cheng, Fei Han

“…Finally, a combined genetic algorithm and gradient projection algorithm (GA-GP) is used to solve the bilevel model, in which the GP algorithm solves the traffic assignment problem with road toll scheme in the lower level. …”
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Impact and compensation of sample clock offset in I-CFDMA uplink by Dan DING, Nai-ping CHENG, Yu-rong LIAO

“…To achieve the sample clock synchronization in the interleaved code and frequency division multiple access(I-CFDMA)uplink,the I-CFDMA uplink model was established,and the disturbance of the sample clock offset(SCO)on the system model was discussed,in addition,the signal time shift,phase rotation,multi-user interference(MUI)and inter-carrier interference(ICI)caused by SCO were analyzed quantitatively.On this basis,a compensation method of multi-user SCO was proposed.For one thing,the relevant metric function was modified considering the SCO of each user; for another thing,a multi-user detection(MUD)algorithm based on harmony search was proposed.This algorithm has a higher efficiency than the commonly-used genetic algorithm(GA),as well as a performance approximate to that of optimal detection without SCO but with <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML"> <mfrac> <mn>1</mn> <mrow> <mn>64</mn></mrow> </mfrac> </math></inline-formula> computational burden.The computer simulation results validate the conclusions obtained.…”
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Optimized Production of Biodiesel Using Internet of Things Sensed Temperature with Hybrid Particle Swarm Optimization by G. Loganathan, M. Kannan

“…The experimental results contrasted with the existent particle swarm optimization (PSO) and genetic algorithm (GA) concerning iteration’s temperature, concentration, production, and fitness. …”
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Optimizing Ontology Alignment through Linkage Learning on Entity Correspondences by Xingsi Xue, Chaofan Yang, Chao Jiang, Pei-Wei Tsai, Guojun Mao, Hai Zhu

“…In this work, an extended compact genetic algorithm-based ontology entity matching technique (ECGA-OEM) is proposed, which uses both the compact encoding mechanism and linkage learning approach to match the ontologies efficiently. …”
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Timetable Design for Urban Rail Line with Capacity Constraints by Yu-Ting Zhu, Bao-Hua Mao, Lu Liu, Ming-Gao Li

“…Then, based on the simulation results, a two-stage genetic algorithm is introduced to find the best timetable. …”
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